Mathematical models for the characterisation of the dynamics of biological systems
The aim of this project is to regard the interaction between biological systems and their environments as a communication channel, and to model and predict the dynamical behaviours of biological systems using techniques of communication theory.
DurationMinimum of 3 years
Full UK tuition fees and a tax-free stipend. This project is on offer in competition with a number of other projects for funding. This opportunity may be available with partial funding for overseas fees for exceptional applicants. However, funding for overseas students is limited and applicants are encouraged to find suitable funding themselves.
Funding sourceUniversity of Surrey
Biological systems are constantly exposed to changing environments and adapt to them. That is, biological systems are capable of gathering information about their environments and processing them. This ability to gather and process information does not require sophisticated organs like the brain of an animal. For instance, slime mould — a large brainless amoeba-like cell — can solve computationally difficult problems in a relatively short time. Or, recent experiments suggest that common bean plants can detect the existence of objects in their vicinities. These, and countless other examples, beg the question how basic biological systems such as a single cell are capable of processing information. The aim of this project is to regard the interaction between biological systems and their environments as a communication channel, and to model and predict the dynamical behaviours of biological systems using techniques of communication theory. A strong background in modern stochastic analysis, and stochastic filtering theory in particular, would be ideal to develop this line of research.
The successful candidate will receive comprehensive research training related to all aspects of the research and opportunities to participate in conferences, workshops and seminars to develop professional skills and research network.
We are able to offer this opportunity starting in October 2021, January 2022, April 2022 or July 2022.
Applicants should have a minimum of a first class honours degree in mathematics, the physical sciences or engineering. Preferably applicants will hold a MMath, MPhys or MSc degree, though exceptional BSc students will be considered.
English language requirements
IELTS minimum 6.5 or above (or equivalent) with 6.0 in each individual category